﻿// NNUE評価関数で用いる入力特徴量とネットワーク構造の定義

#ifndef CLASSIC_NNUE_HALFKPVM_256X2_32_32_H_INCLUDED
#define CLASSIC_NNUE_HALFKPVM_256X2_32_32_H_INCLUDED

#include "../features/feature_set.h"
#include "../features/half_kp_vm.h"

#include "../layers/input_slice.h"
#include "../layers/affine_transform.h"
#include "../layers/affine_transform_sparse_input.h"
#include "../layers/clipped_relu.h"

namespace YaneuraOu {
namespace Eval {

    namespace NNUE {

        // 評価関数で用いる入力特徴量
        using RawFeatures = Features::FeatureSet<
            Features::HalfKP_vm<Features::Side::kFriend>>;

        // 変換後の入力特徴量の次元数
        constexpr IndexType kTransformedFeatureDimensions = 256;

        namespace Layers {

            // ネットワーク構造の定義
            using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
            using HiddenLayer1 = ClippedReLU<AffineTransformSparseInput<InputLayer, 32>>;
            using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
            using OutputLayer = AffineTransform<HiddenLayer2, 1>;

        }  // namespace Layers

        using Network = Layers::OutputLayer;

    }  // namespace NNUE

} // namespace Eval
} // namespace YaneuraOu

#endif // #ifndef NNUE_HALFKPVM_256X2_32_32_H_INCLUDED
